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Linq ToList() and Count() performance problem

I have 200k rows in my table and I need to filter the table and then show in datatable. When I try to do that, my sql run fast. But when I want to get row count or run the ToList(), it takes long time. Also when I try to convert it to list it has 15 rows after filter, it has not huge data.
public static List<Books> GetBooks()
{
List<Books> bookList = new List<Books>();
var v = from a in ctx.Books select a);
int allBooksCount = v.Count(); // I need all books count before filter. but it is so slow is my first problem
if (isFilter)
{
v = v.Where(a => a.startdate <= DateTime.Now && a.enddate>= DateTime.Now);
}
.
.
bookList = v.ToList(); // also toList is so slow is my second problem
}

There's nothing wrong with the code you've shown. So either you have some trouble in the database itself, or you're ruining the query by using IEnumerable instead of IQueryable.
My guess is that either ctx.Books is IEnumerable<Books> (instead of IQueryable<Books>), or that the Count (and Where etc.) method you're calling is the Enumerable version, rather than the Queryable version.
Which version of Count are you actually calling?

First, to get help you need to provide quantitative values for "fast" vs. "too long". Loading entities from EF will take longer than running a raw SQL statement in a client tool like TOAD etc. Are you seeing differences of 15ms vs. 15 seconds, or 15ms vs. 150ms?
To help identify and eliminate possible culprits:
Eliminate the possibility of a long-running DbContext instance tracking too many entities bogging down performance. The longer a DbContext is used and the more entities it tracks, the slower it gets. Temporarily change the code to:
List<Books> bookList = new List<Books>();
using (var context = new YourDbContext())
{
var v = from a in context.Books select a);
int allBooksCount = v.Count(); // I need all books count before filter. but it is so slow is my first problem
if (isFilter)
{
v = v.Where(a => a.startdate <= DateTime.Now && a.enddate>= DateTime.Now);
}
.
.
bookList = v.ToList();
}
Using a fresh DbContext ensures queries are not sifting through in-memory entities after running a query to find tracked instances to return. This also ensures we are running against IQueryable off the Books DbSet within the context. We can only guess what "ctx" in your code actually represents.
Next: Look at a profiler for MySQL, or have your database log out SQL statements to capture exactly what EF is requesting. Check that the Count and ToList each trigger just one query against the database, and then run these exact statements against the database. If there are more than these two queries being run then something odd is happening behind the scenes that you need to investigate, such as that your example doesn't really represent what your real code is doing. You could be tripping client side evaluation (if using EF Core 2) or lazy loading. The next thing I would look at is if possible to look at the execution plan for these queries for hints like missing indexes or such. (my DB experience is primarily SQL Server so I cannot provide advice on tools to use for MySQL)

I would log the actual SQL queries here. You can then use DESCRIBE to look at how many rows it hits. There are various tools that can further analyse the queries if DESCRIBE isn't sufficient. This way you can see whether it's the queries or the (lack of) indices that is the problem. Next step has to be guided by that.

How to really target table at runtime in Entity Framework Core

I have KPI tables and now it has more than 500M rows. I would like to split this table into KPI_Year2011, KPI_Year2012...KPI_2020 (will be created on 1st January 2020).
PS: All tables have same structure and Entity type is KPI.
How would you target table at runtime like this
public IActionResult GetKpis(int year) {
/*var kpis = context.KPI.where(k => k.year == year).ToList(); */
var kpis = context.SetTargetTable($"KPI_Year{year}").ToList();
return View(kpis);
}

For you and your program, logically, it's one big table. And the fact that the database needs to split it into multiple smaller ones to make access faster should be none of your business.
This is called Partitioning and should really be a job of the database.
For example:
Partitioning in SQL Server
Partitioning in Oracle
Partitioning in Postgres
Partitioning in MariaDB
You could manually implement it in your program logic, but that would just mean you reinvent the wheel. In fact, probably a much crappier and tinier wheel that breaks more often and does not really fit onto the rest of your car.
Once you leave this job to the database, your question has a solution: do nothing. Your program does not even know it's multiple tables in the database. It's one partitioned table.

You can use a raw query to implement this. Here is an example.
public IActionResult GetKpis(int year) {
var kpis = context.KPI.FromSql($"SELECT * FROM KPI_Year{year}").ToList();
return View(kpis);
}
Update
For inserting the data, you can use
context.Database.ExecuteSqlCommand($"INSERT INTO KPI_Year{year} VALUES (#col1, #col2)",
new SqlParameter("col1", col1Value),
new SqlParameter("col2", col2Value)
);

Entity Framework bulk insert with updating rows from another table

I'm using Microsoft SQL Server and Entity Framework. I have N (for example 10 000) items to insert. Before inserting each item I need to insert or update existing group. It doesn't work well because of low performance. It's because I'm generating too many queries. Each time in loop I'm looking for group by querying Groups table by three (already indexed) parameters.
I was thinking about querying first all groups by using WHERE IN query (Groups.Where(g => owners.Contains(g.OwnerId) && .. ), but as I remember such queries are limited by number of parameters.
Maybe I should write a stored procedure?
Here is my example code. I'm using IUnitOfWork pattern for wrapping the EF DbContext:
public async Task InsertAsync(IItem item)
{
var existingGroup = await this.unitOfWork.Groups.GetByAsync(item.OwnerId, item.Type, item.TypeId);
if (existingGroup == null)
{
existingGroup = this.unitOfWork.Groups.CreateNew();
existingGroup.State = GroupState.New;
existingGroup.Type = item.Code;
existingGroup.TypeId = item.TypeId;
existingGroup.OwnerId = item.OwnerId;
existingGroup.UpdatedAt = item.CreatedAt;
this.unitOfWork.Groups.Insert(existingGroup);
}
else
{
existingGroup.UpdatedAt = item.CreatedAt;
existingGroup.State = GroupState.New;
this.unitOfWork.Groups.Update(existingGroup);
}
this.unitOfWork.Items.Insert(item);
}
foreach(var item in items)
{
InsertAsync(item);
}
await this.unitOfWork.SaveChangesAsync();

There are three key elements to improve performance when bulk inserting:
Set AutoDetectChangesEnabled and ValidateOnSaveEnabled to false:
_db.Configuration.AutoDetectChangesEnabled = false;
_db.Configuration.ValidateOnSaveEnabled = false;
Break up your inserts into segments, wich use the same DbContext, then recreate it. How large the segment should be varies from use-case to use-case, I made best performance at around 100 Elements before recreating the Context. This is due to the observing of the elements in the DbContext.
Also make sure not to recreate the context for every insert.
(See Slauma's answer here Fastest Way of Inserting in Entity Framework)
When checking other tables, make sure to use IQueryable where possible and to work only where necessary with ToList() or FirstOrDefault(). Since ToList() and FirstOrDefault() loads the objects. (See Richard Szalay's answer here What's the difference between IQueryable and IEnumerable)
These tricks helped me out the most when bulk inserting in a scenario as you described. There are also other possibilities. For example SP's, and the BulkInsert function.

How do I update multiple Entity models in one SQL statement?

I had the following:
List<Message> unreadMessages = this.context.Messages
.Where( x =>
x.AncestorMessage.MessageID == ancestorMessageID &&
x.Read == false &&
x.SentTo.Id == userID ).ToList();
foreach(var unreadMessage in unreadMessages)
{
unreadMessage.Read = true;
}
this.context.SaveChanges();
But there must be a way of doing this without having to do 2 SQL queries, one for selecting the items, and one for updating the list.
How do i do this?

Current idiomatic support in EF
As far as I know, there is no direct support for "bulk updates" yet in Entity Framework (there has been an ongoing discussion for bulk operation support for a while though, and it is likely it will be included at some point).
(Why) Do you want to do this?
It is clear that this is an operation that, in native SQL, can be achieved in a single statement, and provides some significant advantages over the approach followed in your question. Using the single SQL statement, only a very small amount of I/O is required between client and DB server, and the statement itself can be completely executed and optimized by the DB server. No need to transfer to and iterate through a potentially large result set client side, just to update one or two fields and send this back the other way.
How
So although not directly supported by EF, it is still possible to do this, using one of two approaches.
Option A. Handcode your SQL update statement
This is a very simple approach, that does not require any other tools/packages and can be performed Async as well:
var sql = "UPDATE TABLE x SET FIELDA = #fieldA WHERE FIELDB = #fieldb";
var parameters = new SqlParameter[] { ..., ... };
int result = db.Database.ExecuteSqlCommand(sql, parameters);
or
int result = await db.Database.ExecuteSqlCommandAsync(sql, parameters);
The obvious downside is, well breaking the nice linqy paradigm and having to handcode your SQL (possibly for more than one target SQL dialect).
Option B. Use one of the EF extension/utility packages
Since a while, a number of open source nuget packages are available that offer specific extensions to EF. A number of them do provide a nice "linqy" way to issue a single update SQL statement to the server. Two examples are:
Entity Framework Extended Library that allows performing a bulk update using a statement like:
context.Messages.Update(
x => x.Read == false && x.SentTo.Id == userID,
x => new Message { Read = true });
It is also available on github
EntityFramework.Utilities that allows performing a bulk update using a statement like:
EFBatchOperation
.For(context, context.Messages)
.Where(x => x.Read == false && x.SentTo.Id == userID)
.Update(x => x.Read, x => x.Read = true);
It is also available on github
And there are definitely other packages and libraries out there that provide similar support.

Even SQL has to do this in two steps in a sense, in that an UPDATE query with a WHERE clause first runs the equivalent of a SELECT behind the scenes, filtering via the WHERE clause, then applying the update. So really, I don't think you need to be worried about improving this.
Further, the reason why it's broken into two steps like this in LINQ is precisely for performance reasons. You want that "select" to be as minimal as possible, i.e. you don't want to load any more objects from the database into in memory objects than you have to. Only then do you alter objects (in the foreach).
If you really want to run a native UPDATE on the SQL side, you could use a System.Data.SqlClient.SqlCommand to issue the update, instead of having LINQ give you back objects that you then update. That will be faster, but then you conceptually move some of your logic out of your C# code object model space into the database model space (you are doing things in the database, not in your object space), even if the SqlCommand is being issued from your code.

IQueryable<>.ToString() too slow

I'm using BatchDelete found on the answer to this question: EF Code First Delete Batch From IQueryable<T>?
The method seems to be wasting too much time building the delete clause from the IQueryable. Specifically, deleting 20.000 elements using the IQueryable below is taking almost two minutes.
context.DeleteBatch(context.SomeTable.Where(x => idList.Contains(x.Id)));
All the time is spent on this line:
var sql = clause.ToString();
The line is part of this method, available on the original question linked above but pasted here for convenience:
private static string GetClause<T>(DbContext context, IQueryable<T> clause) where T : class
{
const string Snippet = "FROM [dbo].[";
var sql = clause.ToString();
var sqlFirstPart = sql.Substring(sql.IndexOf(Snippet, System.StringComparison.OrdinalIgnoreCase));
sqlFirstPart = sqlFirstPart.Replace("AS [Extent1]", string.Empty);
sqlFirstPart = sqlFirstPart.Replace("[Extent1].", string.Empty);
return sqlFirstPart;
}
I imagine making context.SomeTable.Where(x => idList.Contains(x.Id)) into a compiled query could help, but AFAIK you can't compile queries while using DbContext on EF 5. In thesis they should be cached but I see no sign of improvement on a second execution of the same BatchDelete.
Is there a way to make this faster? I would like to avoid manually building the SQL delete statement.

The IQueryable isn't cached and each time you evaluate it you're going out to SQL. Running ToList() or ToArray() on it will evaluate it once and then you can work with the list as the cached version.
If you want to preserve you're interfaces, you'd use ToList().AsQueryable() and this would pass in a cached version.
Related post.
How do I cache an IQueryable object?

It seems there is no way to cache the IQueryable in this case, because the query contains a list of ids to check against and the list changes in every call.
The only way I found to avoid the two minute delay in building the query every time I had to mass-delete objects was to use ExecuteSqlCommand as below:
var list = string.Join("','", ids.Select(x => x.ToString()));
var qry = string.Format("DELETE FROM SomeTable WHERE Id IN ('{0}')", list);
context.Database.ExecuteSqlCommand(qry);
I'll mark this as the answer for now. If any other technique is suggested that doesn't rely on ExecuteSqlCommand, I'll gladly change the answer.

There is a EF pattern that works Ok.
it uses projection. to return ONLY keys from DB. (projections are not added to context,
So this is pretty quick.
Then You build the context with KEY only stub POCOs, and light the fuse....
basically.
var deleteMagazine = Context.Set<DeadMeat>.Where(t=>t.IhateYou == true).Select(t=>t.THEKEY).toList
//Now instantiate a dummy POCO with KEY only for the list,
foreach ( var bullet in deleteMagazine)
{
context.Set<deadmeat>.attach(bullet);
context.set<deadmeat>.remove(bullet);
// consider saving chnages every 1000 records .... performance, trial different values
if (magazineisEmpty) // your counter logic here :-)
context.SaveChanges
}
// shoot anyone still moving
context.SaveChanges
check SQL server profiler....